Catch all of the talks from MDS Fest 2.0 HERE
This International Women's Day, we're shining a spotlight on the remarkable women who are set to inspire, educate, and lead discussions at the forefront of the data space at this year's MDS Fest.
Read on to learn more about the women speaking at MDS Fest, the purpose of MDS Fest, and why the team behind the conference focuses on gender parity as a cornerstone of MDS Fest.
Now in its second year, MDS Fest 2.0 will return from April 8 - 12, 2024 with an impressive roster of speakers, all accessible for free. The core value of MDS Fest is to provide a platform to amplify voices in the data community, encourage more data enthusiasts, especially first-time speakers, to come together and share their stories.
When we began planning MDS Fest 2.0, it was important for us to prioritize gender parity in our speaker lineup. It’s no secret in the data space that there is a historical underrepresentation of women in the C-suite, a massive disparity in the amount of VC funding for women-led companies, and at conferences in the data space, we’ve seen over and over again speaker lineups that consist of almost entirely male speakers.
We drew inspiration from conferences like DataConnect Conference, a data conference with the speaker lineup reserved exclusively for women. DataConnect Conference ’s mission is to provide visibility to women making an impact in the data and analytics space, and they do so by providing speaking opportunities for women and gender minorities - for 44% of their speakers, it is their first time speaking at a conference. Conferences and spaces like DataConnect are crucial for challenging the status quo that exists today.
Our focus on prioritizing gender parity in our speaker lineup at MDS Fest 2.0 is our commitment to addressing and challenging the systemic barriers and disparities women face in the data space, and to create an inclusive platform where women's voices are not only heard, but celebrated.
This year’s MDS Fest lineup, we are hosting over 50 talks, with 46% of talks by women.
Today, we're shining a spotlight on the 23 remarkable women who are set to inspire, educate, and lead discussions at the forefront of the data space at this year's MDS Fest, and we invite you to join us in celebrating the achievements and contributions of women in the data space.
By highlighting the stories, challenges, and successes of women in data, we hope to inspire a new generation of data scientists, engineers, and leaders, and move towards a more equitable future in data.
Register for MDS Fest at mdsfest.com and get access to all of this year’s programming.
See more about our other tracks and speakers in articles on our blog:
- Elevate your data career: the ultimate guide to career growth and skill development
- What to expect at MDS Fest
- The expert playbook to building a data-driven organization
Playing to Win: Championing data as a product using gamification
A talk by: Abi O , Analytics Principal, Paystack
Date: April 8, 10:00AM ET
Abi will be walking the audience through how the data team think of Data as a Product at Paystack, the team’s data stack, and how they switched up data literacy training with gamification aids.
How notebooks empower citizen data scientists
A talk by: Megan Lieu, Data Advocate, Deepnote
Date: April 8, 12:00PM ET
In the past couple years, the trends that have altered the course of the data industry have been the explosion of data roles, the increase in remote roles, and the rise of AI. These three forces have led to the rise of the Citizen Data Scientist. Our prediction is that the Citizen Data Scientist will become one of the most important roles in data and business teams. In this talk, we’ll discuss how data notebooks can enable these folks to support their teams better, democratize their insights and empower their entire organizations to collaborate better.
AI > BI: Driving decision making with numbers not dashboards
A talk by: Gabi Steele, CEO, Preql
Date: April 8, 12:30PM ET
Join Gabi for a talk is centered on discussing ways to influence business teams by offering them governed access to data instead of merely giving them the opportunity to request new dashboards. We’ll emphasizes the importance of empowering teams with direct access to metrics and figures under a controlled environment, which allows them to make informed decisions without the need to wait for new dashboard creations.
Welcome to data driving school: 5 tips for being data-driven from helping hundreds of companies set up their BI tool
A talk by: Katie Hindson, Head of Product & Data, Lightdash
Date: April 9, 9:30AM ET
Successfully integrating a BI tool plays a huge role in becoming a "data driven" company. For the past 3.5 years, Katie has been helping hundreds of customers set up their BI tool (Lightdash) to help them become more data driven. So, for the past 3.5 years, she has been training as a data driving instructor. Finally, Katie has decided to share some of her favourite lessons from data driving school with a wider audience. Because, they're not just applicable to Lightdash, they're applicable to anyone working in data.
Data Culture: Real experiences in owning errors and educating teams
A talk by: Cecilia Dones, Founder, 3 Standard Deviations
Date: April 9, 10:00AM ET
Data Literacy is a foundational stone in transforming a business via data. Despite investments, data remains underutilized, siloed, and fails to impact decision-making. This talk proposes a paradigm shift: cultivating a Data Culture. Drawing upon psychology, sociology, and anthropology, this talk seeks to explore how to: - Demolish data silos and build cross-functional data communities. - Embed experimental learning to encourage exploration and embrace mistakes. - Empower all stakeholders with a fundamental understanding of data's language. Through real stories of 'Data Tribalism' and how not to deal with data silos and real stories of 'Data Rituals' that foster inclusivity in the data community, attendees will take away actionable lessons to implement within their own organizations.
How marketers at The Zebra self-serve from the data warehouse
A talk by: Cynthia Caridad , Director of Lifecycle, The Zebra
Date: April 9, 10:30AM ET
Intended audience: marketers, and the data teams that enable them. Cynthia is sharing how The Zebra has brought the Modern Data Stack to their marketers. Historically, the biggest blocker for marketing teams was data accessibility: the data team couldn’t keep up with their demands, so it could take months to get new data to drive campaigns.
The Zebra implemented a Composable CDP with Snowflake and Hightouch, and worked hard to fundamentally change their data culture. The marketing team is now fully data-literate and can self-serve - join Cynthia’s talk to learn how they did it.
Your baby is ugly: how to build lineage that is easy to use and easy on the eyes
A talk by: Lindsay Murphy , Head of Data, Secoda
Date: April 9, 11:30AM ET
Data lineage can be one of the most valuable tools in your toolbox when it comes to scaling and maintaining a highly performant data stack. But lineage can be a tough thing to scale. The more assets you add, the more dependencies have to be connected, and things can get confusing–fast.
This problem gets worse when teams build their infrastructure without lineage in mind. All of the hard work you put into building your beautiful stack–actually turns out to be a horrid mess (your baby...it is ugly).
In this session, Lindsay will break down methods for building modularity and layers in your dbt project, to ensure you don't have a nasty surprise when you connect to a column-level lineage tool like Secoda.
Maturing data cultures: From winging it to self-serve data governance
A talk by: Stefania Olafsdottir , CEO & Co-Founder, Avo
Date: April 9, 12:30PM ET
So you want to be an analytics engineer?
A talk by: Madison Schott , Senior Analytics Engineer, ConvertKit
Date: April 9, 1:00PM ET
Are you a data analyst or data engineer looking to explore a career pivot? Analytics engineering may just be for you. In this talk, I will explore the main differences between a data analyst, an analytics engineer, and a data engineer. We will then talk about the main technical skills and soft skills you need to know, and how you can work on developing them, to transition into this role.
Upskilling without pitfalling
A peer exchange session by: Phoenix Millacy Jay , Data & Analytics, /dev/color , and Natalie Nakamine , Analytics Engineer, Retool
Date: April 9, 2:00PM ET
Data Practitioners regardless of being veterans after years of data wrangling or leading teams may struggle to keep up with upskilling in the new paradigm shifts, while early stage folks just finishing up self study, bootcamp or formal study historically struggle with applying these skills to generate scalable business insights. Join this talk and you can add your voice to help determine the flow of discussion around how to upskill as: - a seasoned senior leader managing teams with new tools - a plateaued professional assigned only repetitive projects - a puzzled post-grad breaking into business insights without business context.
How to pivot your data team from a service team to a value-generator
A talk by: Taylor Brownlow , Head of Product, Count
Date: April 10, 9:00AM ET
That sign won't stop me because I can't read: collaborative data literacy solutions at work
A peer exchange session by: Jerrie Kumalah , Resident Architect, dbt Labs , and Faith Lierheimer , Sr. Technical Instructor, dbt Labs
Date: April 10, 10:00AM ET
Session goals:
1. Define and share what data literacy means in various business contexts.
2. Identify specific situations where lack of data literacy hinders the data team's work, again with attention to business context.
3. Have attendees share what achieving some level of data literacy would look like specifically at their organization. If they could wave a magic wand and suddenly have data-literate execs and business stakeholders, what are some behaviors that those data-literate people would engage in?
4. Work backwards from the ideal and identify 2-3 specific strategies to encourage that ideal behavior from your business stakeholders/execs.Each of these 4 topics would be discussed in smaller groups and then shared out with the larger group. The first 2 would be discussed simultaneously in breakout rooms and then returned to the larger group to share, and then the last 2 would be discussed in breakout rooms & returned to the larger group to share out, with volunteers identified to take notes and send to attendees post-session.
Data career roadmap strategies: A what not to do guide
A talk by: Jes Carney, Data Engineering Manager, Brooklyn Data Co. (a Velir company)
Date: April 10, 12:30PM ET
A no-nonsense discussion on navigating the data career landscape, drawing from firsthand experiences mentoring data teams in both enterprise and start-up companies. This talk cuts through the complexity to offer a clear, what-not-to-do guide for aspiring and established data professionals alike. Learn from the missteps and successes encountered on the road to building rewarding careers in data. We'll focus on practical advice for developing essential skills, avoiding typical career pitfalls, and maintaining your drive in the fast-paced world of data.
A new era in B2B data exchange
A talk by: Pardis Noorzad , CEO, General Folders
Date: April 10, 4:30PM ET
Businesses collaborate through data exchange. However, data exchange pipelines are time consuming to build, prone to leaks, difficult to monitor, and costly to audit. In this talk, we present an overview of the why and the how of cross-company data exchange. We then discuss solutions that better match the efficiency and security standards of today.
Women Lead Data with Lindsay Murphy and Julie Beynon
A live podcast recording with Lindsay Murphy , Head of Data, Secoda, and Julie Beynon , Head of Data, Census
Date: April 11, 11:00AM ET
Women Lead Data is a weekly podcast hosted by Lindsay Murphy, Head of Data at Secoda. The podcast aims to share insights about the underrepresentation of women in leadership roles in data, uncover helpful tips and advice for progressing your career in data, understand what it takes to reach the C-level, and inspire women who are curious but not yet sure if this is the right career path for them. Join us for a live podcast episode with Julie Beynon, Head of Data at Census.
Don't get stood up: How to implement data team office hours that people actually want to attend
A talk by: Kelly Burdine, Director of Data Science and Analytics, Wellthy
Date: April 11, 12:00PM ET
For years I've heard data leaders toss around the concept of holding data team office hours. Much like university days, this can be dedicated time when stakeholders can come get help, ask questions, and pick your brain. It also allows the data team to stay more focused outside of office hours. It sounds useful in theory, but what often results is nobody ever showing up to office hours. About 15 months ago, I wanted to give office hours a try at my company. We iterated a bit in the beginning till we found something that worked, but I think I've found right formula. It has been very beneficial for both the data team and our stakeholders in answering adhoc questions, increasing data literacy, and promoting more data driven decision making. In this talk I'd like to share the some tactical tips on how you can implement a successful office hours program at your organization.
Data: The Keystone of AI Safety
A talk by: Sumi Singh, Ph.D., Founder, Generative Artificial Intelligence Labs
Date: April 11, 1:00PM ET
AI technology carries risks that we need to address. This presentation focuses on how data is critical in spotting and handling these risks, covering everything from enterprise security to personal privacy. We'll look at real examples to show how to monitor AI systems, set up safety measures, and keep improving them. We'll discuss how data involves AI risks’ problems and solutions. Everyone is welcome to this talk, whether you're interested in AI or working with it directly. It's all about learning how data impacts AI safety.
Elevating data literacy in small businesses
A talk by: Karen Hsieh, Director of Tech & Data, ALPHA Camp
Date: April 12, 9:00AM ET
This presentation is specifically designed for professionals tasked with establishing or leading data teams in small businesses, especially those in their first data-centric roles.
The data (error) generating process
A talk by: Emily Riederer, Senior Manager of Analytics, Capital One
Date: April 12, 1:00PM ET
Statisticians often approach probabilistic modeling by first understanding the conceptual data generating process. However, when validating messy real-world data, the technical aspects of the data generating process is largely ignored. In this talk, I will argue the case for developing more semantically meaningful and well-curated data tests by incorporating both conceptual and technical aspects of "how the data gets made". To illustrate these concepts, we will explore the NYC subway rides open dataset to see how the simple act of reasoning about real-world events their collection through ETL processes can help craft far more sensitive and expressive data quality checks. I will also illustrate instrumenting such checks based on new features in the dbt-utils package (with the grouping functionality that I contributed). This talk should be of interest to analytics engineers looking for frameworks to improve their data quality. Audience members should leave this talk with a clear framework in mind for ideating better tests for their own pipelines. Prior work inspiring this post come from past blog posts on grouped data checks (https://www.emilyriederer.com/post/grouping-data-quality/) and common causes of error in ETL pipelines (https://www.emilyriederer.com/post/data-error-gen/).
Evolving data pipelines at scale
A talk by: Marisa Smith, PhD , Developer Advocate, Tobiko Data
Date: April 12, 1:30PM ET
The intended audience for this talk is really anyone in the modern data stack space. Starting at beginner level, attendees can expect to learn about the daily problems that our DevOps and Data Engineers face, discuss a new solution in the ecosystem, and show some of the many fantastic developer experience improvements and productivity increases they can get with this OS tool. SQLMesh is a new OS project gaining real traction in the data engineering community because of its ease of use and scalability. However, few people know about it yet, and we want to share the project and its community with others.
Event tracking is the new superpower of product analysts
A talk by: Eva Schreyer , Analytics Manager, Neugelb Studios GmbH
Date: April 12, 2:00PM ET
A sufficient event tracking framework is the most powerful data asset for product analytics. It will make or break your ability to analyse data and to influence your business. Quite often event tracking is a task nobody really wants to own and it is left for the data engineers to figure it out. And then analysts have to deal with data that are hard to use to answer business questions. I would argue that event tracking - as it is a data collection technique as well as a data source for analytics - should be the center of digital product analytics and analytics team should focus much more on building appropriate tracking frameworks from the start. I want to talk about my experience with two very different event tracking approaches (both for mobile apps) and what pros and cons are of various approaches.
Skills data professionals really need
A talk by: Monica Kay Royal , Founder, nerdnourishment
Date: April 12, 2:30PM ET
We will be sharing the most critical skills that data professionals use on a daily basis which almost everyone already has in their toolbelt. This talk will be especially helpful for folks that are interested in a data career as they will learn how they can highlight their existing skills to help them transition into the data field.
Learn more about MDS Fest at mdsfest.com - we hope you will join us!
